Method and apparatus for optimizing electrical stimulation parameters using heart rate variability

ABSTRACT

A cardiac rhythm management system modulates the delivery of pacing and/or autonomic neurostimulation pulses based on heart rate variability (HRV). An HRV parameter being a measure of the HRV is produced to indicate a patient&#39;s cardiac condition, based on which the delivery of pacing and/or autonomic neurostimulation pulses is started, stopped, adjusted, or optimized. In one embodiment, the HRV parameter is used to evaluate a plurality of parameter values for selecting an approximately optimal parameter value.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is related to co-pending, commonly assigned, U.S.patent application Ser. No. ______, entitled “METHOD AND APPARATUS FORUSING HEART RATE VARIABILITY TO CONTROL MAXIMUM TRACKING RATE IN PACINGTHERAPY,” filed on ______ (Attorney Docket No. 279.921US1), U.S. patentapplication Ser. No. ______, entitled “METHOD AND APPARATUS FOR USINGHEART RATE VARIABILITY AS A SAFETY CHECK IN ELECTRICAL THERAPIES,” filedon ______ (Attorney Docket No. 279.922US1), and U.S. patent applicationSer. No. 10/726,062, entitled “CARDIAC RHYTHM MANAGEMENT SYSTEM USINGTIME-DOMAIN HEART RATE VARIABILITY INDICIA,” filed on Dec. 2, 2003,which is hereby incorporated by reference in its entirety.

FIELD OF THE INVENTION

This document generally relates to cardiac rhythm management (CRM)systems and particularly, but not by way of limitation, to such systemsusing heart rate variability (HRV) to control delivery of electricalstimulation pulses.

BACKGROUND

The heart is the center of a person's circulatory system. It includes anelectro-mechanical system performing two major pumping functions. Theleft portions of the heart draw oxygenated blood from the lungs and pumpit to the organs of the body to provide the organs with their metabolicneeds for oxygen. The right portions of the heart draw deoxygenatedblood from the body organs and pump it to the lungs where the blood getsoxygenated. These pumping functions are accomplished by cycliccontractions of the myocardium (heart muscles). In a normal heart, thesinoatrial node generates electrical impulses called action potentialsat a normal sinus rate. The electrical impulses propagate through anelectrical conduction system to various regions of the heart to excitethe myocardial tissues of these regions. Coordinated delays in thepropagations of the action potentials in a normal electrical conductionsystem cause the various portions of the heart to contract in synchronyto result in efficient pumping functions indicated by a normalhemodynamic performance. A blocked or otherwise abnormal electricalconduction and/or deteriorated myocardial tissue cause dysynchronouscontraction of the heart, resulting in poor hemodynamic performance,including a diminished blood supply to the heart and the rest of thebody. The condition where the heart fails to pump enough blood to meetthe body's metabolic needs is known as heart failure.

Electrical stimulation therapies have been applied to restore functionsof the electrical conduction system and reduce the deterioration ofmyocardial tissue. Their potential benefits to a patient are achieved ormaximized when such therapies are adaptive to the patient's cardiacconditions and metabolic needs, both changing over time. In one example,delivering pacing pulses at a relatively high rate may satisfy thepatient's instantaneous metabolic need for participating in an intensephysical activity but result in further deterioration of myocardialtissue. In another example, an electrical therapy preventing furtherdeterioration of myocardial tissue may significantly limit the patient'sexercise capacity when the therapy is being delivered.

For these and other reasons, there is a need to modulate the delivery ofcardiac electrical therapies based on the patient's changing needs andconditions.

SUMMARY

A CRM system modulates the delivery of pacing and/or autonomicneurostimulation pulses based on HRV, which is the variance in cardiaccycle lengths over a predetermined period of time. An HRV parameterbeing a measure of the HRV is produced to indicate a patient's cardiaccondition, based on which the delivery of pacing and/or autonomicneurostimulation pulses is started, stopped, adjusted, or optimized.

In one embodiment, a CRM system includes a pulse output circuit, asensing circuit, an HRV measurement circuit, and a stimulation controlcircuit. The pulse output circuit delivers electrical stimulationpulses. The sensing circuit senses a cardiac signal. The HRV measurementcircuit measures the HRV to produce an HRV parameter. The stimulationcontrol circuit includes a stimulation parameter optimization modulethat adjusts at least one stimulation parameter to an approximatelyoptimal value based on the HRV parameter. The stimulation parameteroptimization module includes a stimulation parameter generator, a pulseoutput controller, and a stimulation parameter selector. The stimulationparameter generator produces a plurality of parameter values for thestimulation parameter. The pulse output controller controls the deliveryof the electrical stimulation pulses using the plurality of parametervalues during a stimulation parameter optimization period. Thestimulation parameter selector selects the approximately optimal valuefor the stimulation parameter from the plurality of parameter values.The approximately optimal parameter value corresponds to a maximum valueof the HRV parameter measured for the stimulation parameter optimizationperiod.

In one embodiment, an HRV-based stimulation parameter optimizationmethod is provided. A stimulation parameter optimization period isstarted. A cardiac signal is sensed. A plurality of parameter values forat least one stimulation parameter are produced. Electrical stimulationpulses are delivered using the plurality of parameter values during thestimulation parameter optimization period. A variance in cardiac cyclelengths is measured over a predetermined period of time to produce atleast one HRV parameter based on the cardiac signal sensed during thestimulation parameter optimization period. An approximately optimalvalue is selected for the stimulation parameter from the plurality ofparameter values. The approximately optimal value corresponds to amaximum value of the HRV parameter measured during the stimulationparameter optimization period.

This Summary is an overview of some of the teachings of the presentapplication and not intended to be an exclusive or exhaustive treatmentof the present subject matter. Further details about the present subjectmatter are found in the detailed description and appended claims. Otheraspects of the invention will be apparent to persons skilled in the artupon reading and understanding the following detailed description andviewing the drawings that form a part thereof, each of which are not tobe taken in a limiting sense. The scope of the present invention isdefined by the appended claims and their equivalents.

BRIEF DESCRIPTION OF THE DRAWINGS

In the drawings, which are not necessarily drawn to scale, like numeralsdescribe similar components throughout the several views. The drawingsillustrate generally, by way of example, but not by way of limitation,various embodiments discussed in the present document.

FIG. 1 is an illustration of an embodiment of a CRM system and portionsof an environment in which the CRM system is used.

FIG. 2 is a block diagram illustrating one embodiment of a stimulationsystem being part of the CRM system.

FIG. 3 is a block diagram illustrating one embodiment of a pacing systembeing part of the CRM system.

FIG. 4 is a block diagram illustrating one embodiment of aneurostimulation system being part of the CRM system.

FIG. 5 is a block diagram illustrating one embodiment of a pacing systemincluding an HRV-based MTR adjustment system.

FIG. 6 is a flow chart illustrating one embodiment of a method foradjusting an MTR using an HRV parameter.

FIG. 7 is a block diagram illustrating one embodiment of a stimulationsystem including an HRV-based stimulation parameter optimization module.

FIG. 8 is a block diagram illustrating one embodiment of the stimulationparameter optimization module.

FIG. 9 is a block diagram illustrating another embodiment of thestimulation parameter optimization module.

FIG. 10 is a flow chart illustrating one embodiment of a method forstimulation parameter optimization using an HRV parameter.

FIG. 11 is a block diagram illustrating one embodiment of a stimulationsystem including an HRV-driven therapy switch system.

FIG. 12 is a flow chart illustrating one embodiment of a method forstarting and stopping a therapy using an HRV parameter.

DETAILED DESCRIPTION

In the following detailed description, reference is made to theaccompanying drawings which form a part hereof, and in which is shown byway of illustration specific embodiments in which the invention may bepracticed. These embodiments are described in sufficient detail toenable those skilled in the art to practice the invention, and it is tobe understood that the embodiments may be combined, or that otherembodiments may be utilized and that structural, logical and electricalchanges may be made without departing from the spirit and scope of thepresent invention. The following detailed description provides examples,and the scope of the present invention is defined by the appended claimsand their equivalents.

It should be noted that references to “an”, “one”, or “various”embodiments in this disclosure are not necessarily to the sameembodiment, and such references contemplate more than one embodiment.

This document discusses, among other things, a CRM system using aclosed-loop system to control delivery of cardiac therapies based on apatient's HRV. HRV is known to indicate autonomic balance between theoutput of the parasympathetic and sympathetic nervous systems, therebyindicating the patient's cardiac condition. Generally, the patient'scardiac condition improves when HRV increases and worsens when HRVdecreases. If the patient suffers left ventricular dysfunction, theautonomic balance shifts toward the sympathetic nervous system, and theHRV decreases. Thus, the closed-loop system modulates the cardiactherapies to increase or maximize the patient's HRV.

HRV is the beat-to-beat variance in cardiac cycle length over a periodof time. An “HRV parameter” as used in this document includes anyparameter being a measure of the HRV, including any qualitativeexpression of the beat-to-beat variance in cardiac cycle length over aperiod of time. In one embodiment, the HRV parameter is the timedifferences between successive cardiac cycle lengths averaged over apredetermined period of time. In one specific embodiment, the cardiaccycle lengths are ventricular cycle lengths, i.e., V-V intervals, or R-Rintervals, which are time intervals between successive ventriculardepolarizations (R waves). In an alternative specific embodiment, thecardiac cycle lengths are atrial cycle lengths, i.e., A-A intervals, orP-P intervals, which are time intervals between successive atrialdepolarizations (P waves). In various specific embodiments, the HRVparameters includes, but are not limited to, Standard Deviation ofNormal-to-Normal intervals (SDNN), Standard Deviation of Averages ofNormal-to-Normal intervals (SDANN), ratio of Low-Frequency (LF) HRV toHigh-Frequency (HF) HRV (LF/HF ratio), HRV footprint, andRoot-Mean-Square of Successive Differences (RMSSD).

Standard Deviation of Normal-to-Normal intervals (SDNN).Normal-to-Normal intervals refer to R-R intervals during a normal sinusrhythm. SNDD is the standard deviation of the R-R intervals measuredover a predetermined time period.

Standard Deviation of Averages of Normal-to-Normal intervals (SDANN).Normal-to-Normal intervals refer to R-R intervals during a normal sinusrhythm. To compute SDANN, R-R intervals are measured and averaged over afirst time period. The standard deviation of the averaged R-R intervalsis computed for a second time period that includes multiple first timeperiods. In one embodiment, measured R-R intervals are averaged overfive-minute periods for 24 hours(i.e., 288 five-minute periods). TheSDANN is the standard deviation of five-minute mean R-R intervalscomputed for the 24-hour period.

Ratio of LF HRV to HF HRV (LF/HF ratio). The LF HRV includes componentsof the HRV having frequencies between about 0.04 Hz and 0.15 Hz. The HFHRV includes components of the HRV having frequencies between about 0.15Hz and 0.40 Hz. The LF/HF ratio is used to track trends in shifts ofautonomic balance. A substantial change in the LF/HF ratio indicates achange in systemic stress that indicates the degree to which thesympathetic nervous system is over-stimulated.

HRV footprint. HRV footprint refers to a histogram of the HRV plottedagainst heart rate. The time difference between successive R-R intervalsare determined for a period of time and plotted versus the heart ratemeasured over that period of time.

Root-Mean-Square of Successive Differences (RMSSD). Root-mean-squarevalues are computed, each for time differences between successive R-Rintervals determined for a period of time.

The HRV parameters discussed above are examples of HRV parameters usedin the closed-loop system that modulates cardiac therapies to increaseor maximize the patient's HRV. One of ordinary skill in the art willunderstand, upon reading and comprehending this document, that otherparameters capable of representing or indicating the HRV can be used asthe HRV, according to the present subject matter.

Some HRV parameters provide for relatively short-term measures of theHRV. Other HRV parameters for relatively long-term measures of the HRV.Certain HRV parameters are capable of providing both short-term andlong-term measures of the HRV with reasonable accuracy. In one exemplaryembodiment, a therapy is delivered to a patient with differentpredetermined values of one or more therapy parameters to evaluate theeffects of the one or more therapy parameters. An HRV parameter ismeasured during the evaluation. The values of one or more therapyparameters that yield the most desirable HRV are selected as the optimalvalues for the patient. To limit the evaluation to a reasonableduration, a suitable HRV parameter provides reasonable accuracy whenused as a short-term measure of the patient's HRV. In another exemplaryembodiment, a therapy is delivered to a patient with one or moredynamically adjusted therapy parameters over a relatively long period oftime, such as 24 hours. An HRV parameter is measured and recorded, withthe values of the one or more therapy parameters applied, during thatperiod of time. This results in a map relating the HRV parameters to thevalues of the one or more therapy parameters, which provides a basis fordetermining optimal therapy parameter values for the patient. In such anembodiment, a suitable HRV parameter provides reasonable accuracy whenused as a long-term measure of the patient's HRV. In general, one ofordinary skill in the art will understand, upon reading andcomprehending this document, that the selection of one or moreparticular HRV parameters depends on the overall design of the methodand system for modulating cardiac therapies based on the HRV.

FIG. 1 is an illustration of an embodiment of a CRM system 100 andportions of an environment in which CRM system 100 is used. System 100includes an implantable system 105, an external system 185, and atelemetry link 180 providing for communication between implantablesystem 105 and external system 185.

Implantable system 105 includes, among other things, implantable medicaldevice 110 and lead system 108. In various embodiments, implantablemedical device 110 is an implantable CRM device including one or more ofa pacemaker, a cardioverter/defibrillator, a cardiac resynchronizationtherapy (CRT) device, a cardiac remodeling control therapy (RCT) device,a neruostimulator, a drug delivery device or a drug delivery controller,and a biological therapy device. As illustrated in FIG. 1, implantablemedical device 110 is implanted in a body 102. In various embodiments,lead system 108 includes leads for sensing physiological signals anddelivering pacing pulses, cardioversion/defibrillation shocks,neurostimulation pulses, and/or pharmaceutical or other substances. Inone embodiment, lead system 108 includes one or more pacing-sensingleads each including at least one electrode placed in or on a heart 101for sensing electrogram and/or delivering pacing pulses. In anotherembodiment, lead system 108 includes one or moreneurostimulation-sensing leads each including at least one electrodeplaced on a nerve of the autonomic nervous system for sensing neuralsignals and delivering neurostimulation pulses. In another embodiment,lead system 108 includes one or more pacing-sensing leads and one ormore neurostimulation-sensing leads to synchronize neurostimulation withintrinsic activities of heart 101 and/or pacing.

In one embodiment, external system 185 is a patient management systemincluding an external device 190, a network 192, and a remote device194. External device 190 is within the vicinity of implantable medicaldevice 110 and communicates with implantable medical device 110bi-directionally via telemetry link 180. Remote device 194 is in aremote location and communicates with external device 190bi-directionally via network 192, thus allowing a user to monitor andtreat a patient from a distant location. In another embodiment, externalsystem 185 includes a programmer communicating with implantable medicaldevice 110 bi-directionally via telemetry link 180.

System 100 includes a stimulation system 115 that uses an HRV parameterfor closed-loop control of stimulation pulse delivery. In oneembodiment, implantable medical device 110 includes a pacemaker thatdelivers pacing pulses to heart 101 to maximize the HRV. In anotherembodiment, implantable medical device 110 includes a neurostimulatorthat delivers neurostimulation pulses to the autonomic nervous system tomaximize the HRV. In another embodiment, implantable medical deviceincludes a pacemaker and a neurostimulator to deliver combined cardiacpacing and autonomic neurostimulation to maximize the HRV. Thedistribution of stimulation system 115 in system 100 depends on designand patient management considerations, such as the size and powerconsumption of each system component and the ability of monitoring thepatient in various settings from various locations. In one embodiment,as illustrated in FIG. 1, implantable medical device 110 includes theentire system 115. This allows implantable system 105 to adjuststimulation parameters in response to changes in an HRV parameterwithout communicating to external system 185. In another embodiment,implantable medical device 110 and external system 185 each includeportions of system 115. Stimulation parameters are adjusted based on anHRV parameter when implantable medical device 110 and external system185 are communicatively coupled via telemetry link 180.

FIG. 2 is a block diagram illustrating one embodiment of stimulationsystem 115. Stimulation system 115 includes a sensing circuit 212, apulse output circuit 214, an HRV measurement circuit 220, and astimulation control circuit 230.

Sensing circuit 212 senses at least a cardiac signal that allows for ameasurement of the HRV. In one embodiment, sensing circuit 212 sensesone or more additional signals each indicative of one or more cardiacfunctions from the heart and/or the autonomic nervous system through oneor more electrodes of lead system 108. Pulse output circuit 214 deliverselectrical stimulation pulses to the heart and/or the autonomic nervoussystem through one or more electrodes of lead system 108. HRVmeasurement circuit 220 measures the HRV and produces at least one HRVparameter based on a signal sensed by sensing circuit 212. In variousembodiments, HRV measurement circuit 220 includes, but is not limitedto, one or more of an SDNN generator to produce an SDNN, an SDANNgenerator to produce an SDANN, an LF/HF ratio generator to produce anLF/HF ratio, an HRV footprint generator to produce an HRV footprint, andan RMSSD generator to produce an RMSSD. In one embodiment, HRVmeasurement circuit 220 includes an autonomic balance monitor to monitoran HRV parameter indicative of a balance between sympathetic andparasympathetic activities. In one specific example, the autonomicbalance monitor includes the LF/HF ratio generator to produce the LF/HFratio as the HRV parameter indicative of the balance between sympatheticand parasympathetic activities. Stimulation control circuit 230 controlsthe delivery of the electrical stimulation pulses from pulse outputcircuit 214 using one or more stimulation parameters that are adjustedor optimized based on the HRV parameter. In one embodiment, stimulationcontrol circuit 230 determines an approximately optimal value for eachadjustable parameter that affects the HRV.

FIG. 3 is a block diagram illustrating one embodiment of a pacing system315, which is a specific embodiment of stimulation system 115. Pacingsystem 315 includes a sensing circuit 312, a pacing output circuit 314,HRV measurement circuit 220, and a pacing control circuit 330.

Sensing circuit 312 is a specific embodiment of sensing circuit 212 andincludes an electrogram sensing circuit. The electrogram sensing circuitsenses one or more atrial and/or ventricular electrograms. Pacing outputcircuit 314 is a specific embodiment of pulse output circuit 214 anddelivers pacing pulses to one or more atrial and/or ventricular sites.Pacing control circuit 330 is a specific embodiment of stimulationcontrol circuit 230 and controls the delivery of the pacing pulses frompacing output circuit 314 using one or more pacing parameters that areadjusted or optimized based on the HRV parameter. In one embodiment,pacing control circuit 330 determines an approximately optimal value foreach adjustable pacing parameter that affects the HRV. Examples of suchadjustable pacing parameters include, but are not limited to,atrioventricular delays (AVDs), interventricular delays (IVDs), andpacing sites (sites to which the pacing pulses are delivered).

FIG. 4 is a block diagram illustrating one embodiment of aneurostimulation circuit 415, which is another specific embodiment ofstimulation system 115. Neurostimulation system 415 includes a sensingcircuit 412, a neurostimulation output circuit 414, HRV measurementcircuit 220, and a neurostimulation control circuit 430.

Sensing circuit 412 is a specific embodiment of sensing circuit 212 andincludes an neural signal sensing circuit in addition to an electrogramsensing circuit. The neural sensing circuit senses one or more neuralsignals from the autonomic nervous system including sympathetic andparasympathetic nerves. The electrogram sensing circuit senses one ormore atrial and/or ventricular electrograms to allow for measurement ofthe HRV. In one embodiment, the one or more atrial and/or ventricularelectrograms also allow for a delivery of neurostimulation that issynchronized to cardiac activities detectable from the one or moreelectrograms. Neurostimulation output circuit 414 is a specificembodiment of pulse output circuit 214 and delivers neurostimulationpulses to one or more nerves of the autonomic nervous system.Neurostimulation control circuit 430 is a specific embodiment ofstimulation control circuit 230 and controls the delivery of theneurostimulation pulses from neurostimulation output circuit 414 usingone or more neurostimulation parameters that are adjusted or optimizedbased on the HRV parameter. In one embodiment, neurostimulation controlcircuit 430 determines an approximately optimal value for eachadjustable pacing parameter that affects the HRV. Examples of suchadjustable neurostimulation parameters include, but are not limited to,stimulation frequencies, stimulation amplitudes, and stimulation sites(sites to which the neurostimulation pulses are delivered).

In another specific embodiment, stimulation system 115 is a combinationof pacing system 315 and neurostimulation system 415, and implantablemedical device 110 is an implantable pacemaker-neurostimulator. In thisembodiment, sensing circuit 212 combination of sensing circuits 312 and412, pulse output circuit 214 is a combination of pacing output circuit314 and neurostimulation circuit 414, and stimulation control circuit230 is a combination of pacing control circuit 330 and neurostimulationcircuit 430. In one embodiment, stimulation system 115 delivers pacingand neurostimulation pulses in a temporally coordinated manner toimprove or optimize the HRV parameter.

In the following examples, specific embodiments of stimulation system115, including pacing system 315, neurostimulation system 415, and thecombination thereof, are discussed to illustrate, but not to restrict,the use of an HRV parameter for stimulation control according to thepresent subject matter.

EXAMPLE 1 HRV-Based Maximum Tracking Rate (MTR) Adjustment

A decreased HRV indicates that a patient has a worsened or worseningcardiac condition and should therefore limit exercise intensity. In amulti-channel (including dual-channel) pacemaker pacing in an atrialtracking mode (such as VDD or DDD mode), the ventricular pacing ratetracks the atrial rate up to a programmed maximum tracking rate (MTR).The MTR prevents the ventricles from being paced to a potentiallyharmful rate, for example, when atrial tachycardia or atrialfibrillation occurs. When a patient exercises, the sinus rate increases,and the atrial tracking mode pacing drives the ventricular rate toincrease with the sinus rate within the limit set by the MTR. Theincreased ventricular rate results in increased blood flow to the bodyto meet the patient's increased metabolic need for oxygen. If the MTR isset too high, when the patient's exercise intensity reaches a certainlevel, the pacing may allow the patient to continue or furtherincreasing the intensity of exercise even when doing so puts thepatient's heart at risk. If the MTR is adequately set, the ventricularrate stops increasing at an exercise intensity tolerable by the heart,and the patient feels the need to either stop exercising or stopincreasing exercise intensity. Thus, an adequately set MTR prevents thepacing from providing the patient with an exercise capacity that is at apotentially harmful level. Because patient's cardiac condition includingthe tolerance to exercise changes over time, an MTR adjusted base on thepatient's HRV is capable of maximizing benefits of pacing withoutcausing harmful effects to the heart.

FIG. 5 is a block diagram illustrating one embodiment of a pacing system515 including an HRV-based MTR adjustment system. Pacing system 515 is aspecific embodiment of pacing system 315 and includes sensing circuit312, pacing output circuit 314, HRV measurement circuit 220, and apacing control circuit 530.

Pacing control circuit 530 includes an MTR adjustment module 532 and apacing algorithm execution module 534. MTR adjustment module 532 adjustsan MTR based on an HRV parameter. In one embodiment, as illustrated inFIG. 5, MTR adjustment module 532 includes an MTR selector 536 to selecta value for the MTR from a plurality of predetermined values based on anHRV parameter produced by HRV measurement circuit 220. In oneembodiment, a higher value and a lower value for the MTR and a thresholdHRV level are determined for a patient based on the patient's cardiaccondition. MTR adjustment module 532 receives the HRV parameter from HRVmeasurement circuit 220 and compares the HRV parameter to the thresholdHRV level. MTR selector 536 sets the MTR to the higher value if the HRVparameter exceeds the threshold HRV level and the lower value if the HRVparameter does not exceed the threshold HRV level. In anotherembodiment, three of more substantially different values for the MTR andtwo or more threshold HRV levels are determined for a patient to providea finer control of MTR based on the HRV parameter. In a furtherembodiment, MTR adjustment module 532 includes an HRV thresholdgenerator to dynamically adjust the threshold HRV level(s) based on anindication, estimation, or prediction of the patient's activity level.In one specific embodiment, the HRV threshold generator adjusts one ormore threshold HRV levels based on the patient's heart rate. In anotherembodiment, the HRV threshold generator adjusts one or more thresholdHRV levels based the patient's anticipated activity level duringspecific times of each day.

Pacing algorithm execution module 534 controls the delivery of pacingpulses from pacing output circuit by executing an atrial tracking pacingalgorithm that uses the MTR. Pacing algorithm execution module 534includes, but is not limited to, one or more of a bradycardia pacingalgorithm execution module, a CRT pacing algorithm execution module, andan RCT pacing algorithm execution module. One of such pacing algorithmexecution modules is activated to execute one of the pacing algorithmsat an instant. In one embodiment, CRT pacing provides for anapproximately optimal hemodynamic performance, and RCT pacing reducesthe degree of post MI remodeling. In one embodiment, a CRT pacingalgorithm is executed with one or more pacing parameters approximatelyoptimized to maximize a measure of hemodynamic performance, for example,as a treatment improving quality of life for a heart failure patient. AnRCT pacing algorithm is executed to reduce the degree of remodeling byredistributing the loading or stress on the LV wall, for example, as apost myocardial infarction (MI) treatment.

FIG. 6 is a flow chart illustrating one embodiment of a method foradjusting an MTR using an HRV parameter. In one embodiment, the methodis performed by pacing system 515.

A cardiac signal is sensed at 600. The cardiac signal is indicative ofcardiac depolarizations and allows for a measurement of the HRV. In oneembodiment, the cardiac signal includes an atrial electrogram or aventricular electrogram.

The HRV is measured based on the sensed cardiac signal, and at least oneHRV parameter is produced based on the HRV measurement, at 610. In oneembodiment, atrial depolarizations are detected from an atrialelectrogram. Atrial intervals between successive atrial depolarizationare measured. The HRV parameter is calculated based on the atrialintervals. In another embodiment, ventricular depolarizations aredetected from a ventricular electrograms. Ventricular intervals betweensuccessive ventricular depolarization are measured. The HRV parameter iscalculated based on the ventricular intervals.

An atrial tracking pacing algorithm is executed to control a delivery ofpacing pulses at 620. The atrial tracking pacing algorithm uses an MTR.Examples of the atrial tracking pacing algorithm include a bradycardiapacing algorithm, a CRT pacing algorithm, and a RCT pacing algorithm.

The MTR is adjusted based on the HRV parameter at 630. In oneembodiment, the MTR is set to one of a plurality of predetermined valuesbased on the HRV parameter. In one specific embodiment, the HRVparameter is compared to a threshold HRV level. The MTR is set to afirst value if the HRV parameter exceeds the predetermined threshold HRVlevel and a second value if the HRV parameter does not exceed thethreshold HRV level. The first value is substantially higher than thesecond value to allow for a higher exercise intensity when the HRV ishigher. In one embodiment, the threshold HRV level is dynamicallyadjusted based on an indication, estimation, or prediction of thepatient's activity level. In one specific embodiment, the threshold HRVlevel is adjusted based on the patient's heart rate. In anotherembodiment, the threshold HRV level is adjusted based the patient'santicipated activity level during specific times of each day.

EXAMPLE 2 HRV-Based Therapy Parameter Optimization

Because HRV is indicative of a patient's cardiac condition, an HRVparameter is capable of indicating effects of an electrical stimulationtherapy including pacing therapy, autonomic neurostimulation therapy,and a combination of the pacing and autonomic neurostimulationtherapies. To maximize the benefit of the therapy, therapy parametersare adjusted for the maximum HRV practically achievable by deliveringelectrical stimulation pulse to the patient's heart and/or autonomicnervous system.

FIG. 7 is a block diagram illustrating one embodiment of a stimulationsystem 715 that includes an HRV-based stimulation parameter optimizationmodule. Stimulation system 715 is a specific embodiment of stimulationsystem 115 and includes sensing circuit 212, pulse output circuit 214,HRV measurement circuit 220, and a stimulation control circuit 730.

Stimulation control circuit 730 includes a stimulation parameteroptimization module 731 that adjusts at least one stimulation parameterto an approximately optimal value based on at least one HRV parameterproduced by HRV measurement circuit 220. In one embodiment, stimulationcontrol circuit 730 includes a pacing control circuit that includes apacing parameter optimization module to adjust at least one pacingparameter to an approximately optimal value based on the HRV parameter.The pacing parameter optimization module includes, but is not limitedto, one or more of an AVD optimization module to optimize an AVD, an IVDoptimization module to optimize an IVD, and a pacing site optimizationmodule to optimize a selection of one or more sites to which the cardiacpacing pulses are delivered. In general, the pacing parameteroptimization module allows optimization of any pacing parameter whosevalue affects the HRV by adjusting that parameter for a maximum HRVindicated by the HRV parameter. In another embodiment, stimulationcontrol circuit 730 includes a neurostimulation control circuit thatincludes a neurostimulation parameter optimization module to adjust atleast one neurostimulation parameter to an approximately optimal valuebased on the HRV parameter. The neurostimulation parameter optimizationmodule includes, but is not limited to, one or more of a stimulationpulse frequency optimization module to optimize a stimulation frequencyand a stimulation sites optimization module to optimize a selection ofone or more sites to which the neurostimulation pulses are delivered. Ingeneral, the neurostimulation parameter optimization module allowsoptimization of any neurostimulation parameter whose value affects theHRV by adjusting that parameter for a maximum HRV indicated by the HRVparameter.

In one embodiment, HRV measurement circuit 220 continuously updates theHRV parameter to reflect changes in the patient's cardiac condition, andstimulation parameter optimization module 731 adjusts the stimulationparameter to the approximately optimal value based on the HRV parameteron a continuous basis. In another embodiment, stimulation parameteroptimization module 731 determines the approximately optimal value forthe stimulation parameter based on the HRV parameter during astimulation parameter optimization period. This period is startedaccording to a predetermined schedule, such as on a programmed periodicbasis, or is started in response to a command, such as a command enteredby a physician or other caregiver. Stimulation parameter optimizationmodule 731 includes a stimulation parameter generator 738, a pulseoutput controller 740, and a stimulation parameter selector 742.Stimulation parameter generator 738 produces a plurality of parametervalues for the stimulation parameter that is to be optimized. Pulseoutput controller 740 controls the delivery of electrical stimulationpulses using the plurality of parameter values during the stimulationparameter optimization period. Stimulation parameter selector 742selects an approximately optimal value for the stimulation parameterfrom the plurality of parameter values. The approximately optimal valueis the value corresponding to a maximum value of the HRV parameterobtained with pacing using the plurality of parameter values. Specificexamples of stimulation parameter optimization module 731 that optimizesat least one stimulation parameter during a stimulation parameteroptimization period are discussed below with reference to FIGS. 8 and 9.

FIG. 8 is a block diagram illustrating one embodiment of a stimulationparameter optimization module 831, which is one embodiment ofstimulation parameter optimization module 731. Stimulation parameteroptimization module 831 includes an optimization timer 846, astimulation parameter generator 838, a pulse output controller 840, anda stimulation parameter selector 842. Stimulation parameter optimizationmodule 831 determines an approximately optimal value for at least onestimulation parameter by delivering test stimulation pulses using aplurality of predetermined values for the stimulation parameter whilemeasuring the HRV and selects the value for the stimulation parameterthat corresponds to a maximum value of the HRV parameter. As oneembodiment of stimulation parameter optimization module 731, stimulationparameter optimization module 831 is applicable for optimization ofpacing parameters, neurostimulation parameters, or both.

Optimization timer 846 starts the stimulation parameter optimizationperiod during which the test stimulation pulses are delivered and theapproximately optimal value for the stimulation parameter is determined.In one embodiment, optimization timer 846 starts the stimulationparameter optimization period according to a predetermined schedule,such as on a periodic basis. In one embodiment, optimization timer 846is programmed to start the stimulation parameter optimization periodwhen the patient is at rest, such as during sleeping time. In anotherembodiment, optimization timer 846 starts the stimulation parameteroptimization period as requested by a person such as a physician, othercaregiver, or the patient. The stimulation parameter optimization periodends when the approximately optimal value for the stimulation parameteris selected.

Stimulation parameter generator 838 produces the plurality of values forthe stimulation parameter. In one embodiment, as illustrated in FIG. 8,stimulation parameter generator 838 includes a physiologic parametermeasurement module 844 that measures at least one physiologic parameterrelated to the patient's cardiac condition. Examples of the physiologicparameter include the heart rate and a time interval between twodetectable cardiac electrical and/or mechanical events. Stimulationparameter generator 838 produces the plurality of values for thestimulation parameter based on the measured physiologic parameter.

Pulse output controller 840 controls the delivery of stimulation pulsesusing the plurality of values produced for the stimulation parameterduring the stimulation parameter optimization period. Pulse outputcontroller 840 includes a stimulation algorithm execution module tocontrol the delivery of stimulation pulses by executing a stimulationalgorithm using the stimulation parameter. The stimulation algorithm isexecuted to control the delivery of a plurality of stimulation pulseseries. Each stimulation pulse series includes a plurality ofstimulation pulses to be delivered using one of the plurality of valuesproduced for the stimulation parameter. In one embodiment, eachstimulation pulse series is preceded by a non-stimulation period toestablish a baseline HRV, such that the effect of stimulation for thatstimulation pulse series can be substantially isolated. In variousembodiments, the stimulation algorithm execution module includes one ormore of a bradycardia pacing algorithm execution module, a CRT pacingalgorithm execution module, an RCT pacing algorithm execution module, anautonomic neurostimulation algorithm execution module, and a combinedpacing-neurostimulation algorithm execution module. One of suchalgorithm execution modules is activated at an instant.

Stimulation parameter selector 842 selects the approximately optimalvalue for the stimulation parameter from the plurality of parametervalues. HRV measurement circuit 220 produces the HRV parameter for thestimulation parameter optimization period. Each value produced andtested for the stimulation parameter is associated with one or morevalues of the HRV parameter. Stimulation parameter selector 842 selectsthe approximately optimal value for the stimulation parameter as thevalue corresponding to a maximum value of the HRV parameter produced forthe stimulation parameter optimization period.

In one exemplary specific embodiment, physiologic parameter measurementmodule 844 includes an atrioventricular interval (AVI) measurementmodule to measure an AVI as an intrinsic time interval between an atrialdepolarization and a successive ventricular depolarization. Stimulationparameter generator 838 produce a plurality of values of an AVD based onthe AVI. Pulse output controller 840 includes a pacing output controllerto control the delivery of a plurality of series of pacing pulses, witheach value produced for the AVD being used for one or more series of theplurality of series of pacing pulses. Stimulation parameter selector 842includes a pacing parameter selector that selects an approximatelyoptimal value from the plurality of values produced for the AVD. Theapproximately optimal value is the value corresponding to a maximumvalue of the HRV parameter produced for the stimulation parameteroptimization period.

When two or more stimulation parameters are to be optimized, stimulationparameter generator 838 produces a plurality of values for eachstimulation parameter. Pulse output controller 840 controls the deliveryof a plurality of series of stimulation pulses. Each series ofstimulation pulses is delivered using a combination of values producedfor all the stimulation parameters to be optimized. Stimulationparameter selector 842 selects an approximately optimal combination ofvalues for all the stimulation parameters to be optimized. Theapproximately optimal combination of values is the combination of valuescorresponding to a maximum value of the HRV parameter produced for thestimulation parameter optimization period.

FIG. 9 is a block diagram illustrating another embodiment of astimulation parameter optimization module 931, which is anotherembodiment of stimulation parameter optimization module 731. Stimulationparameter optimization module 931 includes an optimization timer 946, astimulation parameter generator 938, a pulse output controller 940, anda stimulation parameter selector 942. Stimulation parameter optimizationmodule 931 determines and selects an approximately optimal value for atleast one dynamic stimulation parameter by delivering stimulation pulsesusing dynamically produced values for the dynamic stimulation parameterwhile measuring the HRV. The dynamically produced values of the dynamicstimulation parameter are evaluated by their effect on an HRV parameter.As one embodiment of stimulation parameter optimization module 731,stimulation parameter optimization module 931 is applicable foroptimization of pacing parameters, neurostimulation parameters, or both.

Optimization timer 946 starts the stimulation parameter optimizationperiod during which the values for the dynamic stimulation parameter aredynamically produced and evaluated and the approximately optimal valuefor the stimulation parameter is determined. In one embodiment,optimization timer 946 starts the stimulation parameter optimizationperiod according to a predetermined schedule, such as on a periodicbasis. In another embodiment, optimization timer 946 starts thestimulation parameter optimization period as requested by a person suchas a physician, other caregiver, or the patient. Optimization timer 946stops the stimulation parameter optimization period after apredetermined period of time. The approximately optimal value for thestimulation parameter is selected at the end of the stimulationparameter optimization period. In one embodiment, the stimulationparameter optimization period covers a period in which a wide variety ofactivities are anticipated for the patient, such as a period of 24hours.

Stimulation parameter generator 938 dynamically produces the values forthe dynamic stimulation parameter. In one embodiment, as illustrated inFIG. 9, stimulation parameter generator 938 includes a physiologicparameter measurement module 944 and a dynamic stimulation parametergenerator 948. Physiologic parameter measurement module 944 measures atleast one physiologic parameter related to the patient's cardiaccondition. Dynamic stimulation parameter generator 948 dynamicallyproduce values of the dynamic stimulation parameter based on thephysiologic parameter.

Pulse output controller 940 controls the delivery of stimulation pulsesusing the dynamically produced values of the dynamic stimulationparameter. Pulse output controller 940 includes a stimulation algorithmexecution module to control the delivery of stimulation pulses byexecuting a stimulation algorithm using the dynamic stimulationparameter whose value is updated each time when the dynamically producedvalue differs from the value being used. In various embodiments, thestimulation algorithm execution module includes one or more of abradycardia pacing algorithm execution module, a CRT pacing algorithmexecution module, an RCT pacing algorithm execution module, an autonomicneurostimulation algorithm execution module, and a combinedpacing-neurostimulation algorithm execution module. One of suchalgorithm execution modules is activated at an instant.

Stimulation parameter selector 942 selects the approximately optimalvalue for the stimulation parameter from the dynamically producedvalues. HRV measurement circuit 220 produces the HRV parameter for thestimulation parameter optimization period. Each dynamically producedvalue for the stimulation parameter is associated with one or morevalues of the HRV parameter. Stimulation parameter selector 942 selectsthe approximately optimal value for the stimulation parameter as thevalue corresponding to a maximum value of the HRV parameter produced forthe stimulation parameter optimization period.

In one exemplary specific embodiment, physiologic parameter measurementmodule 944 includes a heart rate monitor that monitors the patient'sheart rate during the stimulation parameter optimization period. Dynamicstimulation parameter generator 948 includes a dynamic AVD generator todynamically produce values of a dynamic AVD as a function of the heartrate. Pulse output controller 940 includes a pacing output controller tocontrol the delivery of pacing pulses using the dynamic AVD during thestimulation parameter optimization period. Stimulation parameterselector 942 includes a pacing parameter selector that selects anapproximately optimal AVD value being the value of the dynamic AVDcorresponding to a maximum value of the HRV parameter produced for thestimulation parameter optimization period.

When two or more dynamic stimulation parameters are to be optimized,stimulation parameter generator 938 dynamically produces values for allthese dynamic stimulation parameters. Pulse output controller 940controls the delivery of stimulation pulses using a combination of thedynamically produced values for all the dynamic stimulation parameters.Each unique combination of the dynamically produced values for thestimulation parameter is associated with one or more values of the HRVparameter. Stimulation parameter selector 942 selects an approximatelyoptimal combination of values for the stimulation parameters as theunique combination that corresponds to a maximum value of the HRVparameter produced for the stimulation parameter optimization period.

FIG. 10 is a flow chart illustrating one embodiment of a method forstimulation parameter optimization using an HRV parameter. In oneembodiment, the method is performed by stimulation system 715.

A stimulation parameter optimization period is started at 1000. Thisstarts the process of optimizing at least one stimulation parameter asillustrated in FIG. 10. The stimulation parameter optimization periodlasts until the process is completed. The stimulation parameterincludes, but not limited to, an AVD, an IVD, pacing sites,neurostimulation pulse frequency, and neurostimulation sites.

A signal indicative of a cardiac function is sensed at 1010. The signalincludes one or more of an atrial electrogram, a ventricularelectrogram, a neural signal indicative of sympathetic neuralactivities, and a signal indicative of parasympathetic neuralactivities. At least one cardiac signal allowing for measurement of anHRV parameter is sensed.

A plurality of parameter values for the stimulation parameter isproduced at 1020. In one embodiment, a physiologic parameter related toa patient's cardiac condition is measured at the beginning of thestimulation parameter optimization period. The plurality of parametervalues are calculated based on the physiological parameter. In anotherembodiment, a physiologic parameter related to a patient's cardiaccondition is monitored throughout the stimulation parameter optimizationperiod. The value for the stimulation parameter is dynamicallycalculated as a function of the physiological parameter, which changesdynamically during the stimulation parameter optimization period.

Electrical stimulation pulses are delivered using the plurality ofparameter values at 1030. In one embodiment, pacing pulses aredelivered. In another embodiment, neurostimulation pulses are delivered.In another embodiment, pacing and neurostimulation pulses are deliveredin a temporally coordinated manner. The electrical stimulation pulsesare delivered by executing a stimulation algorithm during thestimulation parameter optimization period. The stimulating algorithmuses the stimulation parameter that is to be optimized. Examples of thestimulation algorithm include, but are not limited to a bradycardiapacing algorithm, a CRT pacing algorithm, an RCT pacing algorithm, anautonomic neurostimulation algorithm, and a combinedpacing-neurostimulation algorithm.

The HRV is measured based on the sensed cardiac signal, and at least oneHRV parameter is produced based on the HRV measurement, at 1040. In oneembodiment, the sensed cardiac signal is an atrial electrogram, and theHRV parameter is produced based on atrial intervals measured from theatrial electrogram. In another embodiment, the sensed cardiac signal isa ventricular electrogram, and the HRV parameter is produced based onventricular intervals measured from the ventricular electrogram.

An approximately optimal parameter value for the stimulation parameteris selected from the plurality of parameter values produced during thestimulation parameter optimization period at 1050. The approximatelyoptimal parameter value corresponding to a maximum value of the HRVparameter produced for the stimulation parameter optimization period.

EXAMPLE 3 HRV-Driven Therapy On/Off Switch

The benefit of an electrical stimulation therapy may depend on apatient's cardiac condition and physical activity level, both changingover time. To maximize the benefit to the patient, the therapy need tobe adaptive to the patient's condition and needs. Some patients receivetwo or more therapies cannot or should not be administeredsimultaneously. The HRV provides for a signal triggering the start,stop, and/or adjustment of therapies. In one embodiment, an HRVparameter is used as a safety check on the delivery of a therapy. Thedelivery of the therapy is suspended when the HRV parameter indicatesthat continued delivery of the therapy is potentially harmful to thepatient. In another embodiment, an HRV parameter is monitored as asignal indicative of a need to switch from one therapy to another inresponse to a change in the patient's condition.

For example, a patient having suffered MI has a decreased hemodynamicperformance and goes through an adverse cardiac remodeling process. Inone embodiment, a CRT is delivered to improve the post MI patient'shemodynamic performance, and an RCT is delivered to reduce the post MIremodeling. Generally, the CRT and RCT cannot be deliveredsimultaneously because of conflicts between their effects. The RCTtreats post MI patients by controlling the progress of post MIremodeling by reducing the preload in the infarct region. Pacing pulsesare delivered with a short AVD to reduce the stress to this region priorto contraction. However, pacing with the short AVD may result in reducedhemodynamic performance. For example, if the heart being paced with theshort AVD has a normal ventricular conduction (Purkinje) system, thepacing lowers the degree of ventricular synchrony and the cardiacoutput, which are measures of hemodynamic performance. One consequentproblem is that when a post MI patient becomes active, the pacing withthe short AVD may limit the cardiac output and hence, prevent the heartfrom pumping sufficient blood to meet the patient's metabolic need. Onesolution is to deliver the CRT and RCT on an alternating basis,depending on the instantaneous metabolic need of the post MI patient,such that the pacing provides for optimal hemodynamic performance whenthe metabolic need is high, and post MI remodeling control when themetabolic need is low. In one embodiment, an HRV parameter is used tocontrol the timing for switching between the CRT and RCT. In onespecific embodiment, when the HRV parameter falls below a threshold, thepatient stops receiving the RCT and starts to receive the CRT. In onespecific embodiment, the HRV parameter is used in combination withanother one or more parameters, such as a physical activity levelparameter, to control the timing for switching between the CRT and RCT.In another embodiment, an RV bradycardia pacing is delivered to improvethe post-MI patient's hemodynamic performance, and the RCT is deliveredto reduce the degree of post MI remodeling. The HRV parameter is used tocontrol the timing for switching between the RV bradycardia pacing andRCT in substantially the same manner as discussed above, with the CRTbeing replaced with the RV bradycardia pacing.

FIG. 11 is a block diagram illustrating one embodiment of a stimulationsystem 1115 with an HRV-driven therapy switch system. Stimulation system1115 is a specific embodiment of stimulation system 115 and includessensing circuit 212, pulse output circuit 214, HRV measurement circuit220, and a stimulation control circuit 1130.

Stimulation control circuit 1130 includes a stimulation algorithmexecution module 1150 and a safety check module 1152. Stimulationalgorithm execution module 1150 controls the delivery of the electricalstimulation pulses by executing at least one stimulation algorithm. As aspecific embodiment of stimulation system 115, stimulation system 1115includes one or both of a pacing system and a neurostimulation system.Stimulation algorithm execution module 1150 includes one or more of abradycardia pacing algorithm execution module, a CRT pacing algorithmexecution module, an RCT pacing algorithm execution module, aneurostimulation algorithm execution module, and a combinedpacing-neurostimulation algorithm execution module. One of suchalgorithm execution module is activated at an instant.

Safety check module 1152 stops the execution of the stimulationalgorithm based on the HRV parameter produced by HRV measurement circuit220. In one embodiment, as illustrated in FIG. 11, safety check module1152 includes a comparator 1154 and a switch circuit 1156. Comparator1154 receives the HRV parameter from HRV measurement circuit 220 andcompares the HRV parameter to a safety threshold. Switch circuit 1156stops the execution of the stimulation algorithm when the HRV parameterfalls below the safety threshold. In a further embodiment, switchcircuit 1156 resumes the execution of the stimulation algorithm when theHRV parameter exceeds another safety threshold. The values of the twosafety thresholds are determined based on specific considerations incardiac condition management and can be equal or different. In oneexemplary specific embodiment, the stimulation algorithm is the RCTpacing algorithm. Safety check module 1152 stops the executing of theRCT pacing algorithm when the patient's HRV indicates or suggests aworsening hemodynamic performance. In another exemplary specificembodiment, the stimulation algorithm is the bradycardia pacingalgorithm. Safety check module 1152 stops the executing of thebradycardia pacing algorithm when the patient's HRV indicates orsuggests that the pacing negatively affects the patient's cardiaccondition.

In another embodiment, switch circuit 1156 stops the execution of afirst stimulation algorithm and starts the execution of a secondstimulation algorithm when the HRV parameter falls below a first safetythreshold, and stops the execution of the second stimulation algorithmand starts the execution of the first stimulation algorithm when the HRVparameter exceeds a second safety threshold. Depending on specificcardiac condition management considerations, the first safety thresholdcan be higher than, equal to, or lower than the second safety threshold.In one exemplary specific embodiment, the first stimulation algorithm isthe RCT pacing algorithm, and the second stimulation algorithm is theCRT pacing algorithm. In another exemplary specific embodiment, thefirst stimulation algorithm is the RCT pacing algorithm, and the secondstimulation algorithm is the bradycardia pacing algorithm.

In one embodiment, safety check module 1152 includes a safety thresholdgenerator to dynamically adjust the safety threshold(s) based on anindication, estimation, or prediction of the patient's activity level.In one specific embodiment, the safety threshold generator adjusts oneor more safety thresholds based on the patient's heart rate. In anotherembodiment, the safety threshold generator adjusts one or more safetythresholds based the patient's anticipated activity level duringspecific times of each day.

FIG. 12 is a flow chart illustrating one embodiment of a method forstarting and stopping a therapy using an HRV parameter. In oneembodiment, the method is performed by stimulation system 1115.

A signal indicative of a cardiac function is sensed at 1200. The signalincludes one or more of an atrial electrogram, a ventricularelectrogram, a neural signal indicative of sympathetic neuralactivities, and a signal indicative of parasympathetic neuralactivities. At least one cardiac signal allowing for measurement of anHRV parameter is sensed.

The HRV is measured based on the sensed cardiac signal, and at least oneHRV parameter is produced based on the HRV measurement, at 1210. In oneembodiment, the sensed cardiac signal is an atrial electrogram, and theHRV parameter is produced based on atrial intervals measured from theatrial electrogram. In another embodiment, the sensed cardiac signal isa ventricular electrogram, and the HRV parameter is produced based onventricular intervals measured from the ventricular electrogram.

Electrical stimulation pulses are delivered by executing a stimulationalgorithm at 1220. Examples of the stimulation algorithm includes abradycardia pacing algorithm, a CRT pacing algorithm, an RCT pacingalgorithm, a neurostimulation algorithm, and a combinedpacing-neurostimulation algorithm.

The execution of the stimulation algorithm is stopped when the HRVparameter is out of a safety window at 1230. In one embodiment, the HRVparameter is compared to a safety threshold. The execution of the firststimulation algorithm is stopped when the HRV parameter falls below thesafety threshold. In a further embodiment, the execution of thestimulation algorithm is resumed when the HRV parameter exceeds anothersafety threshold. In another embodiment, the execution of a firststimulation algorithm is stopped, and the execution of a secondstimulation algorithm is started, when the HRV parameter falls below afirst safety threshold. The execution of the first stimulation algorithmis started, and the execution of the second stimulation algorithm isstopped, when the HRV parameter exceeds a second safety threshold.

In one embodiment, the safety window is dynamically adjusted based on anindication, estimation, or prediction of the patient's activity level.In one specific embodiment, the safety window is adjusted based on thepatient's heart rate. In another embodiment, the safety window isadjusted based the patient's anticipated activity level during specifictimes of each day.

It is to be understood that the above detailed description, includingExamples 1-3, is intended to be illustrative, and not restrictive. Otherembodiments, including any possible permutation of the system componentsdiscussed in this document, will be apparent to those of skill in theart upon reading and understanding the above description. The scope ofthe invention should, therefore, be determined with reference to theappended claims, along with the full scope of equivalents to which suchclaims are entitled.

1. A cardiac rhythm management system comprising: a pulse output circuitto deliver electrical stimulation pulses; a sensing circuit to sense acardiac signal; a heart rate variability (HRV) measurement circuit,coupled to the sensing circuit, to measure an HRV being a variance incardiac cycle lengths over a predetermined period of time based on thesensed cardiac signal and to produce an HRV parameter based on the HRVmeasurement; and a stimulation control circuit, coupled to the pulseoutput circuit, the sensing circuit, and the HRV measurement circuit,the stimulation control circuit including a stimulation parameteroptimization module adapted to adjust at least one stimulation parameterto an approximately optimal value based on the HRV parameter, thestimulation parameter optimization module including: a stimulationparameter generator adapted to produce a plurality of parameter valuesfor the at least one stimulation parameter; a pulse output controlleradapted to control the delivery of the electrical stimulation pulsesusing the plurality of parameter values during a stimulation parameteroptimization period; and a stimulation parameter selector adapted toselect the approximately optimal value for the at least one stimulationparameter from the plurality of parameter values, the approximatelyoptimal parameter value corresponding to a maximum value of the HRVparameter measured for the stimulation parameter optimization period. 2.The system of claim 1, wherein the stimulation parameter optimizationmodule comprises an optimization timer to start the stimulationparameter optimization period.
 3. The system of claim 2, wherein theoptimization timer is programmed to start the stimulation parameteroptimization period on a periodic basis.
 4. The system of claim 2,wherein the stimulation parameter generator comprises a physiologicparameter measurement circuit adapted to measure at least onephysiologic parameter, and wherein the stimulation parameter generatoris adapted to produce the plurality of parameter values for the at leastone stimulation parameter based on the at least one physiologicparameter, and wherein the pulse output controller is adapted to controlthe delivery of the plurality of electrical stimulation pulse serieseach including a plurality of electrical stimulation pulses to bedelivered using one parameter value of the plurality of parameter valuesduring the stimulation parameter optimization period.
 5. The system ofclaim 2, wherein the optimization timer is further adapted to stop thestimulation parameter optimization period.
 6. The system of claim 5,wherein the stimulation parameter generator comprises a physiologicparameter measurement module to measure at least one physiologicparameter and a dynamic stimulation parameter generator to dynamicallyproduce parameter values of at least one dynamic stimulation parameterbased on the at least one physiologic parameter, the pulse outputcontroller is adapted to control the delivery of electrical stimulationpulses using the dynamically produced parameter values of the at leastone dynamic stimulation parameter, and the stimulation parameterselector is adapted to identify an approximately optimal value being avalue of the dynamic stimulation parameter corresponding to a maximumvalue of the HRV parameter measured for the stimulation parameteroptimization period.
 7. The system of claim 1, wherein the pulse outputcontroller comprises a stimulation algorithm execution module to controlthe delivery of the electrical stimulation pulses by executing astimulation algorithm during the stimulation parameter optimizationperiod.
 8. The system of claim 7, wherein the stimulation algorithmexecution module comprise a bradycardia pacing algorithm executionmodule.
 9. The system of claim 7, wherein the stimulation algorithmexecution module comprise a cardiac resynchronization therapy (CRT)pacing algorithm execution module.
 10. The system of claim 7, whereinthe stimulation algorithm execution module comprise a remodeling controltherapy (RCT) pacing algorithm execution module.
 11. The system of claim7, wherein the stimulation algorithm execution module comprise anautonomic neurostimulation algorithm execution module.
 12. The system ofclaim 7, wherein the stimulation algorithm execution module comprise acombined pacing and neurostimulation algorithm execution module.
 13. Thesystem of claim 1, wherein the pulse output circuit comprises a pacingoutput circuit to deliver cardiac pacing pulses, and the stimulationcontrol circuit comprises a pacing control circuit including a pacingparameter optimization module to adjust at least one pacing parameter toan approximately optimal value based on the HRV parameter.
 14. Thesystem of claim 13, wherein the pacing parameter optimization modulecomprises an atrioventricular delay (AVD) optimization module adapted tooptimize one or more AVDs.
 15. The system of claim 13, wherein thepacing parameter optimization module comprises an interventricular delay(IVD) optimization module adapted to optimize one or more IVDs.
 16. Thesystem of claim 13, wherein the pacing parameter optimization modulecomprises a pacing site optimization module adapted to optimize aselection of one or more sites to which the cardiac pacing pulses aredelivered.
 17. The system of claim 1, wherein the pulse output circuitcomprises a neurostimulation circuit to deliver neurostimulation pulses,and the stimulation control circuit comprises a neurostimulation controlcircuit including a neurostimulation parameter optimization module toadjust at least one neurostimulation parameter to an approximatelyoptimal value based on the HRV parameter.
 18. The system of claim 17,wherein the neurostimulation parameter optimization module comprises astimulation pulse frequency optimization module adapted to optimize oneor more stimulation pulse frequencies.
 19. The system of claim 17,wherein the neurostimulation parameter optimization module comprises astimulation site optimization module adapted to optimize a selection ofone or more sites to which the neurostimulation pulses are delivered.20. The system of claim 1, wherein the HRV measurement circuit comprisesone or more of a Standard Deviation of Normal-to-Normal intervals (SDNN)generator to produce an SDNN, a Standard Deviation of Averages ofNormal-to-Normal intervals (SDANN) generator to produce an SDANN, aRatio of Low Frequency HRV to High Frequency HRV ratio (LF/HF ratio)generator to produce an LF/HF ratio, an HRV footprint generator toproduce an HRV footprint, and a Root-Mean-Square of SuccessiveDifferences (RMSSD) generator to produce an RMSSD.
 21. The system ofclaim 1, wherein the HRV measurement circuit comprises an autonomicbalance monitor to monitor a parameter indicative of a balance betweensympathetic and parasympathetic activities.
 22. The system of claim 21,wherein the autonomic balance monitor comprises a Ratio of Low FrequencyHRV to High Frequency HRV ratio (LF/HF ratio) generator to produce anLF/HF ratio.
 23. A method comprising: starting a stimulation parameteroptimization period; sensing a cardiac signal; producing a plurality ofparameter values for at least one stimulation parameter; deliveringelectrical stimulation pulses using the plurality of parameter valuesfor the at least one stimulation parameter during the stimulationparameter optimization period; measuring a variance in cardiac cyclelengths over a predetermined period of time to produce at least oneheart rate variability (HRV) parameter based on the cardiac signalsensed during the stimulation parameter optimization period; selectingan approximately optimal value for the at least one stimulationparameter from the plurality of parameter values, the approximatelyoptimal value corresponding to a maximum value of the HRV parametermeasured during the stimulation parameter optimization period.
 24. Themethod of claim 23, wherein starting the stimulation parameteroptimization period comprises starting the stimulation parameteroptimization period on a periodic basis.
 25. The method of claim 23,further comprising programming the stimulation parameter optimizationperiod for a period associated with low physical activity level.
 26. Themethod of claim 23, further comprising measuring a physiologicparameter, and wherein producing the plurality of parameter values forthe at least one stimulation parameter comprises producing the pluralityof parameter values for the at least one stimulation parameter based onthe measured physiologic parameter, and delivering the electricalstimulation pulses comprises delivering a plurality of stimulation pulseseries each including a plurality of stimulation pulses to be deliveredusing one parameter value of the plurality of parameter values duringthe stimulation parameter optimization period.
 27. The method of claim23, further comprising measuring a dynamically changing physiologicparameter, and wherein producing the plurality of parameter valuescomprises dynamically producing values of a dynamic stimulationparameter based on the dynamically changing physiologic parameter duringthe stimulation parameter optimization period, delivering the electricalstimulation pulses comprises delivering stimulation pulses using thevalues of the dynamic stimulation parameter during the stimulationparameter optimization period, and selecting the approximately optimalvalue for the at least one stimulation parameter including comprisesselecting the approximately optimal value from the values of the dynamicstimulation parameter produced during the stimulation parameteroptimization period, the approximately optimal value corresponding to amaximum value of the HRV parameter measured for the stimulationparameter optimization period.
 28. The method of claim 23, whereindelivering electrical stimulation pulses comprises delivering pacingpulses.
 29. The method of claim 28, wherein delivering pacing pulsescomprises delivering the pacing pulses by executing a pacing algorithmduring the stimulation parameter optimization period, the pacingalgorithm using the at least one stimulation parameter.
 30. The methodof claim 29, wherein executing the pacing algorithm comprises executingat least one of a bradycardia pacing algorithm, a cardiacresynchronization therapy (CRT) pacing algorithm and a remodelingcontrol therapy (RCT) pacing algorithm.
 31. The method of claim 30,wherein the at least one stimulation parameter comprises anatrioventricular delay (AVD).
 32. The method of claim 30, wherein the atleast one stimulation parameter comprises an interventricular delay(IVD).
 33. The method of claim 30, wherein the at least one stimulationparameter comprises a pacing site parameter identifying sites to whichthe pacing pulses are delivered.
 34. The method of claim 23, whereindelivering the electrical stimulation pulses comprises deliveringneurostimulation pulses.
 35. The method of claim 34, wherein deliveringneurostimulation pulses comprises delivering the neurostimulation pulsesby executing a neurostimulation algorithm during the stimulationparameter optimization period, the neurostimulation algorithm using theat least one stimulation parameter.
 36. The method of claim 35, whereinthe at least one stimulation parameter comprises a stimulationfrequency.
 37. The method of claim 35, wherein the at least onestimulation parameter comprises a stimulation site parameter identifyingsites to which the neurostimulation pulses are delivered.
 38. The methodof claim 23, wherein measuring HRV to produce the HRV parametercomprises measuring HRV to produce one or more of a Standard Deviationof Normal-to-Normal intervals (SDNN), a Standard Deviation of Averagesof Normal-to-Normal intervals (SDANN), a Ratio of Low Frequency HRV toHigh Frequency HRV ratio (LF/HF ratio), an HRV footprint, and aRoot-Mean-Square of Successive Differences (RMSSD).
 39. The method ofclaim 23, wherein measuring HRV to produce the HRV parameter comprisesmeasuring HRV to produce a parameter indicative of a balance betweensympathetic and parasympathetic activities.
 40. The method of claim 39,wherein measuring HRV to produce the parameter indicative of the balancebetween sympathetic and parasympathetic activities comprises producing aRatio of Low Frequency HRV to High Frequency HRV ratio (LF/HF ratio).